{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# pyzmq perf crossover\n",
    "\n",
    "Sample plots from running `python collect.py` script to generate performance data.\n",
    "\n",
    "PyZMQ's zero-copy implementation has a nontrivial overhead, due to the requirement to notify Python garbage collection when libzmq is done with a message from its IO thread. Performance optimizations over time and application/machine circumstances change where the crossover is, where zero-copy is more cost than benefit.\n",
    "\n",
    "In general, it is recommended to only use zero-copy for 'large' messages (at least 10s-100s of kB) because the bookkeeping overhead is significantly greater than small `memcpy` calls."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pickle\n",
    "\n",
    "plt.ion()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Throughput\n",
    "\n",
    "Throughput tests measure sending messages on a PUSH-PULL pair as fast as possible. These numbers count the time from first `recv` to the last."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('thr.pickle', 'rb') as f:\n",
    "    thr = pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x116848908>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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trW09tVgSAMC6JBgDAGhgo22NaYsBAPVEMAYA0MhG2RrTFgMA6om3UgIANKg1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\nK7ff88RPDlETwLQNEYy9OckxrbWtKw1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GAAAAAOiSYAwAAACALgnGAAAAAOiSYAwAAACA\nLgnGAAAAAOiSYAwAAACALgnGAAAAAOiSYAwAAACALgnGAAAAAOiSYAwAAACALgnGAAAAAOiSYAwA\nAACALgnGAAAAAOiSYAwAAACALgnGAAAAAOiSYAwAAACALgnGAAAAAOiSYAwAAACALgnGAAAAAOiS\nYAwAAACALgnGAAAAAOiSYAwAAACALgnGAAAAAOiSYAwAAACALgnGAAAAAOjS3LQL+GHQWjsjyYOT\nfHvR4ddU1cunUxEAAAAAu0swtnbPqao/m3YRAAAAAEzGzAZjrbXDkpyb5IiqusEKY+aSnJjk8UkO\nT/KVJG9P8sKq+vZycwAAAACYDTO5x1hr7Y5JLkpyp1WGnpXkuUnOSPKwJKckeWyS88ah2WIvbq19\nqbX22dbacRMuGQAAAIA9bOaCsdbaMUk+kOTLSV69i3G/kqQleVhVvaSqzq2qVyW5b5K7JXnKouGv\nS3K7qrpJkmOTvKS19otD/Q4AAAAADG/mgrEkj0vyiSTHJPn6Lsb9ZpJtVfXexQer6lNJ3pbkSYuO\n/b+q+u/x9xcneV6SEyZcNwAAAAB70CwGY09K8sCq+tZKA1preye5Z5ILVhjy/iS3b63daIXzH09y\n890pEgAAAIDpmrlgrKquqqrvrDLssCQHZhRwLedj489bJUlr7bZLzt8hyb9tuEgAAAAApm5m30q5\nihuOP1d61PKK8echrbVbJvloa+1hVfU345DspUl+faOLf/CDH/yNjc7dLLZv335oMhu/CwDwg9zr\nAWC2zdK9fp999tnw3JnrGFujg8afV61wfuH4wVV1WZJfSfLy1trlSd6Z5Heq6oJhSwQAAABgSL12\njC3sP3bACucPHH9+M0mq6n1J7jKpxY866qjXT+pa07KQKM/C7wIA/CD3egCYbbN0r//whz980kbn\n9toxdt2jkiucX+1RSwAAAAB+yPUajH0pydVZuQts4fhle6YcAAAAAPa0LoOxqvpukg8kufcKQ45O\n8s9V9ZU9VhQAAAAAe1SXwdjY65Ic3Vq73+KDrbXbJ3nk+DwAAAAAM6rXzfdTVWe31s5OcnZr7Q+S\nXJzk1kmem+TjSV49zfoAAAAAGFa3wdjYr2YUhD0hyU2TfDXJW5OcVFXXTrMwAAAAAIY108FYVZ2c\n5ORdnL82yYvGXwAAAAB0pOc9xgAAAADo2Ex3jAEAAAD06pTzL9t6+kWXH7vLQRdsO2m5w4+/++Hn\nPP2YW14ySGGbiI4xAAAAgBl0wtFHXHqDA+auWO+8Gxwwd8UJRx9x6RA1bTaCMQAAAIAZtN/cXjsf\nuvXG29Y776Fbb7xtv7m9dg5R02YjGAMAAACYUevtGuupWywRjAEAAADMrPV2jfXULZYIxgAAAABm\n2lq7xnrrFksEYwAAAAAzba1dY711iyWCMQAAAICZt1rXWI/dYolgDAAAAGDmrdY11mO3WCIYAwAA\nAOjCSl1jvXaLJYIxAAAAgC6s1DXWa7dYIhgDAAAA6MbSrrGeu8USwRgAAABAN5Z2jfXcLZYkc9Mu\nAAAAAIA954Sjj7j0G1/9j/sufD/teqZJMAYAAADQkf3m9tr5gJvtdeXC99OuZ5o8SgkAAABAl3SM\nAQAAAMygU86/bOvpF11+7C4HXbDtpOUOP/7uh5/z9GNueckghW0iOsYAAAAAZtDSN1CuVU9vqhSM\nAQAAAMygpW+gXKue3lQpGAMAAACYUevtGuupWywRjAEAAADMrPV2jfXULZYIxgAAAABm2lq7xnrr\nFksEYwAAAAAzba1dY711iyWCMQAAAICZt1rXWI/dYolgDAAAAGDmrdY11mO3WCIYAwAAAOjCSl1j\nvXaLJcnctAsAAAAAYPL23faSrft95DXHLvx8UJKLk2T/JQPnc8Ocmt9bfOiauz35nO0///xLhq9y\nunSMAQAAAMyg7fd4xqU79/+RVd9GudTO/X/kiu33eEYXHWSCMQAAAIBZNLf/zmuPfOSqb6Nc6toj\nH7ktc/t3sd+YYAwAAABgBi19lHKt9vvIa47dd9tLtg5R02YjGAMAAACYQR6lXJ1gDAAAAGAWeZRy\nVYIxAAAAgBm13q6xnrrFEsEYAAAAwOxaZ9dYT91iiWAMAAAAYKattWust26xRDAGAAAAMNvW2DXW\nW7dYIhgDAAAAmHmrdY312C2WCMYAAAAAZt8qXWM9doslgjEAAACALqzUNdZrt1giGAMAAADowwpd\nY712iyWCMQAAAIBuLO0a67lbLBGMAQAAAPRjSddYz91iSTI37QIAAAAA2HO23+MZl372K9+8b5Ic\n1nG3WCIYAwAAAOjL3P47//2wh1yZJId13C2WeJQSAAAAgE4JxgAAAADokmAMAAAAgC4JxgAAAADo\nkmAMAAAAgC4JxgAAAADokmAMAAAAgC4JxgAAAADokmAMAAAAgC4JxgAAAADo0ty0C+CH07ve9a5D\nk+Soo46adikAwADc6wFgtrnXj+gYAwAAAKBLgjEAAAAAuiQYAwAAAKBLgjEAAAAAuiQYAwAAAKBL\ngjEAAAAAuiQYAwAAAKBLgjEAAAAAuiQYAwAAAKBLgjEAAAAAurRlfn5+2jV04/zzz/cPGwAAAGAA\nxxxzzJb1ztExBgAAAECXdIwBAAAA0CUdYwAAAAB0STAGAAAAQJcEYwAAAAB0STAGAAAAQJcEYwAA\nAAB0STAGAAAAQJcEYwAAAAB0STAGAAAAQJfmpl0As6u1dmiS05LcI8mOJH+T5OlV9e2pFgYATERr\n7d5JXpHk0CRXJ3l1VZ021aIAgEG01t6T5M5Vdfi0a5kkHWMM6awkn0tyiyS3y+jft1dMtSIAYCJa\na3slOSHJM6rqiCRHJXlCa+3+Uy0MAJi41tqDkuw97TqGoGOM79NaOyzJuUmOqKobrDBmLsmJSR6f\n5PAkX0ny9iQvXOgGa61tSfKWJG+rqh1JdrTWTk3ytuF/CwBgJZO611fVziSPWJhTVVe01v4uydYk\n7x30lwAAVjSpe/2isfslOTnJk5OcM1zl06FjjOu01u6Y5KIkd1pl6FlJnpvkjCQPS3JKkscmOW/8\nhytVNV9VZ1TV1Yvm3TnJv066bgBgbSZ5r1/m2j+Z5Jgk75pUvQDA+gx0r3/WePzXJlrsJqFjjCRJ\na+2YJGcn+XSSv8joD8Ry434lSUvygKp676Lj70vy8SRPSfKqZebdIskfZvQHDgDYw4a617fW7pDk\nwiQHJzm+qvwlGABMwRD3+tbazZI8NMndk9x0yPqnRccYCx6X5BMZ/U3v13cx7jeTbFv8hydJqupT\nGT0m+aSlE1prP57k/CQvraoPTaxiAGA9BrnXV9WnquqQJHdL8oLW2n0nWjUAsFZD3OtPSfK7VXXt\nhGvdNARjLHhSkgdW1bdWGtBa2zvJPZNcsMKQ9ye5fWvtRovm3DTJ3yY5tar+ZHLlAgDrNMi9fkFV\nfSLJSzPafwQA2PMmeq9vrR2d5MCqOm/ilW4iHqUkSVJVV61h2GFJDsyotXI5Hxt/3irJV1trN8mo\nU+xVQjEAmK5J3+tba1cluXlV/eOi81cmud7GqwQANmqA/68/Msm9WmvfGB/bK8n1xz8/uqr+7+7U\nu1kIxliPG44/V2rJvGL8eUhr7UeTvC+jUOxPB68MAJiENd/rM3r75DmttftW1aWttR/LaBPfPxy4\nRgBg49Z8r6+q05KctnCitXZEkg9U1eHDlbfnCcZYj4PGnyul0AvHD05yVJLbJjmxtXbiojHXVNXt\nBqoPANg9a77XV9V7WmtPSfLm1trBSa5O8sqqeuvQRQIAG7ae/6/vgmCM9Vh4TvmAFc4fOP78ZlW9\nJ8k+w5cEAEzQmu/1SVJVb0/y9qGLAgAmZl33+sWq6rNJZqpbLLH5Puuz+PGJ5azWkgkAbG7u9QAw\n29zrlxCMsR5fyugxibuscH7h+GV7phwAYMLc6wFgtrnXLyEYY82q6rtJPpDk3isMOTrJP1fVV/ZY\nUQDAxLjXA8Bsc6//QYIx1ut1SY5urd1v8cHW2u2TPHJ8HgD44eVeDwCzzb1+EZvvsy5VdXZr7ewk\nZ7fW/iDJxUlundHr2T+e5NXTrA8A2D3u9QAw29zrv59gjI341Yz+wDwhyU2TfDXJW5OcVFXXTrMw\nAGAi3OsBYLa5149tmZ+fn3YNAAAAALDH2WMMAAAAgC4JxgAAAADokmAMAAAAgC4JxgAAAADokmAM\nAAAAgC4JxgAAAADokmAMAAAAgC4JxgAAAADokmAMAAAAgC4JxgAAAADokmAMAAAAgC4JxgAAAADo\nkmAMAAAAgC4JxgAAAADokmAMAICJaa0d0Vq7/gSuc/PW2n6TqAkAYCVz0y4AAID1a62dm+Qnkvxs\nVf3ntOtJktbaliRvTnK9JD81PnZykpOWDN2R5EtJLkvy9iSvr6rti65ziyQfTfLHSV46eOEAQLd0\njAEA/HC6RZIfS3LgtAtZ5LFJjkry1mXOnZ7kheOvlyb5qyS3S/InSS5srR20aOznk3w5yfNaa4cN\nWjEA0DUdYwAAP5zukuSAqrpi2oUkSWttryQvSvKFJKcuM+QNVfWBJXOun+ScJMckeUGSZyVJVe1o\nrT1vfO6ZSZ4+YOkAQMd0jAEA/BCqqqs3Syg29oAkN0/yyqr6zlomVNW3kzxx/OPDl5z7iyT/mOSx\nrbV9J1koAMACwRgAAJPwxCTfSXLGeiZV1WeTfDXJTZY5/fokhyZ5yG7WBgCwLMEYAAC7pbW2T5IH\nJnn3ervYWmtzSa6f5IvLnH5TRhv1P3C3iwQAWIY9xgAANpHW2m2SPD/JfTLaXP/zSf48ycuq6ppF\n485I8riq2jL++Ygk/77K5R9fVWcsusa+SZ6c5LiM3nB5bZJPJDmtqs5eR9k/leSAJO9fx5wFT8jo\nBQLvWHqiqv6rtXZxRhv6AwBMnGAMAGCTaK3dKskHMwqK3pnRmxnvl+SkJHdN8uBdTP9GRm98XOqg\nJL+TUej1sUVr3TDJeUl+JslHkrw6ycFJ7pHkHa2111bVk9dY+j3GnxeuZXBrbUuSw5M8alzzh5L8\n/grDL0zytNbaoVX1tTXWAwCwJoIxAIDN4zlJfjTJvRbe4Nha2zvJW5N8qrW2V1XtXG5iVX0jyclL\nj7fWzkyyJcnvVdWli069OaM3Wx5fVWcuGr/X+Dq/11r7cFWdvoa6bzX+/NddjLmwtbbc8bcmOaGq\n/nuFeZ8Zf948iWAMAJgoe4wBAGweNxt/fnLhQFXtSNKq6qSVQrGVtFESdVySC5K8YtHxe2e0b9fz\nF4di4/V2ZtShdnGS565xqUOTfKeqrt7FmNMz6g5b+PrjJH+V5GFJLmutPWqFeQt7lh2yxloAANZM\nxxgAwObx4ST3T/KW1tpJST5WVfNVNb/eC7XWDk/y2owesTxuSaj20PHna5ebW1XzrbULk/zv1trN\nqurzqyx3w3wvwFrJGxa64JbUeeskf53kTa21y6rqoiVDBGMAwGAEYwAAm8eLk9w+oy6qX0zyn621\nbUkqydvXGpCNH4d8Y5IfSfKoqvrCkiG3Hn9+c4XHGxe7aUYvANiV7Un2W0ttS1XVv7bWfjvJXyZ5\napKlwdjCda8JAMCECcYAADaJqtqe5OGttbsmeVBGb6Z8SEZB2cOTrJpijT1zPPesqnrLCmN2ZOUN\n7xf70hrGfD3JDVprWzbS3Zbvvc3yTsucu+H40/5iAMDECcYAADaZqvpoko8meWFr7cYZdX89orX2\nwKo6b1dzW2s/lVHn2eeTnLDCsE9n1JH2pqr6twmU/LUke2cUYn19A/MXwrTl9lA7dPz51Q1cFwBg\nl2y+DwCwibTWDlj8c1V9Ocmp4x+PXMPcszL6y8/HVtU3Vxj6zvHn7+7iWndsrW1ZU9HJwtsu77LG\n8Us9ZPz5oWXO/XSSK/O9t1MCAEyMYAwAYBNore3TWvuLJOe21q6/5PSDxp+fXeUyr8hoj7I/qqpt\nKw2qqguTvDvJ8a2154z3JFtcyy9ltNfXK5abv4yFQOuoNY5fvNb9MnoJwDVJXrnMkHsl+fvx2zkB\nACbKo5QAAJtAVV3bWvuHJM9L8i+ttXOSXJVR2PRzGe3Ddc5K81trD0jylCTXJtnRWjt5mWEXV9XC\nNY5P8p4kL0vyqNba3yTZkuTu4/X+Kckfr7H2z7TWvpLkwUmWWzdJfm0cgiWjv5w9LKNusDsn+XaS\nVlX/vOR3OjLJ4Un+z1rqAABYL8EYAMAmUVXPb619LMlvJXl0kn0y6hJ7QZJTx5vzr+Tnxp/7ZBSu\nLefMjMO1qvqv1tq9kzwxyXFJfmM85tNJTkzyqqpaz5sg35bkqa21u473SFvq8Ut+/kaSyzPqSju1\nqi5fZs6Txp9nraMOAIA12zI/v5EXBwEAwPe01u6Y0V5jZ1bV8RO43kEZBWefqKp77+71AACWY48x\nAAB2W1X9Q5JtSR7TWvuJCVzy2Un+R5LTJnAtAIBlCcYAAJiUZ2b035cv252LtNYOS/I7Sd5fVe+Y\nRGEAAMsRjAEAMBFV9ZEkr07y9t281FxGb8X8rd0uCgBgF+wxBgAAAECXdIwBAAAA0CXBGAAAAABd\nEowBAAAA0CXBGAAAAABdEowBAAAA0CXBGAAAAABdEowBAAAA0CXBGAAAAABdEowBAAAA0CXBGAAA\nAABdEowBAAAA0CXBGAAAAABdEowBAAAA0CXBGAAAAABdEowBAAAA0CXBGAAAAABd+v9/PAZZ0+Lq\ntAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116848c50>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 384,
       "width": 611
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for copy, df in thr.groupby('copy'):\n",
    "    plt.loglog(df['size'], df.throughput, 'v', label='copy' if copy else 'nocopy')\n",
    "plt.xlabel('size (B)')\n",
    "plt.ylabel('throughput (msgs/sec)')\n",
    "plt.legend(loc=0)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Scaled plot, showing ratio of zero-copy to copy throughput performance:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x119378ef0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+oX3KqIbajT89/+DZ40fUb0u6XAAAoG8RgAIA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      "text/plain": [
       "<matplotlib.figure.Figure at 0x118f68518>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 401,
       "width": 592
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "copy_mean = thr[thr['copy']].groupby('size').throughput.mean()\n",
    "no_copy = thr[thr['copy'] == False]\n",
    "reference = copy_mean[no_copy['size']]\n",
    "plt.semilogx(no_copy['size'], (no_copy.throughput / reference.data), '-v')\n",
    "plt.ylim(0, 1.2)\n",
    "plt.xlabel(\"size (B)\")\n",
    "plt.title(\"Zero-copy Throughput (normalized to with-copy performance for same size)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the above plot, zero-copy can introduce a 25-50% performance penalty for messages less than 1k.\n",
    "\n",
    "**Note:** Missing from this report is the observed sender-side performance, where zero-copy has the biggest advantage due to the absence of `memcpy` in the `socket.send()` call."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Latency\n",
    "\n",
    "Latency tests measure REQ-REP request/reply cycles, waiting for a reply before sending the next request."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('lat.pickle', 'rb') as f:\n",
    "    lat = pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9yiuOsfPnxYP3r06DA/Pz/tiSeeKFm6dGmAt8ZmMpm0/v372z3LRo8ebe3du3eL559/3sxgGhER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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1193876a0>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 384,
       "width": 617
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import math\n",
    "\n",
    "lat = lat.sort_values(by=['count'], ascending=False)\n",
    "\n",
    "for size, bysize in lat.groupby('size', sort=True):\n",
    "#     plt.figure()\n",
    "    y_max = 0\n",
    "    y_min = np.inf\n",
    "    for copy, data in bysize.groupby('copy', sort=False):\n",
    "        mark = '-' + ('v' if copy else '^')\n",
    "        copy_s = 'copy' if copy else 'nocopy'\n",
    "        if size >= 1e6:\n",
    "            size_s = '%i MB' % (size // 1e6)\n",
    "        elif size >= 1e3:\n",
    "            size_s = '%i kB' % (size // 1e3)\n",
    "        else:\n",
    "            size_s = '%i B' % size\n",
    "        msgs_sec = 1e6 / data['latency']\n",
    "        plt.loglog(data['count'], msgs_sec, mark, label='%s-%s' % (copy_s, size_s))\n",
    "        tic_below = 10**int(math.log(msgs_sec.min(), 10))\n",
    "    \n",
    "    plt.legend(loc=0)\n",
    "\n",
    "    plt.xlabel('msg count')\n",
    "    plt.ylabel('req/rep msgs/sec')\n"
   ]
  }
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